Search

As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of "carbon neutrality". However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy. [ABSTRACT FROM AUTHOR]

Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area's precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen's Slope in the baseline and future periods with all RCPs. [ABSTRACT FROM AUTHOR]

Owing to limited research on the interactions between cropland vegetation and climate and irrigation, this study used the normalized difference vegetation index (NDVI) as a cropland vegetation indicator to describe vegetation dynamics. Potential evapotranspiration (PET) was calculated using the Penman–Monteith equation. A partial correlation analysis and a Pearson correlation coefficient were used to determine the spatial response mechanisms of cropland vegetation to different climatic factors and irrigation in China for the period 1985–2015. The results show that different climatic factors (precipitation, PET, and water deficits) display positive correlations with cropland vegetation in China. A stronger correlation was observed between cropland vegetation and meteorological factors in northern China compared to the southern parts; the response time of NDVI values of croplands to precipitation was observed to be short-term (1 to 3 months) and long-term (3 to 6 months) in northern and southern regions, respectively. In contrast, the response time of NDVI values of croplands to PET displayed a complex spatial heterogeneity. Most of the cropland vegetation and the areas with the highest potential crop yields were located in the eastern part of China; these areas also require higher levels of irrigation, which benefits the potential crop yields. This study can provide a better understanding of the agricultural ecosystems and formulate strategies for food security. [ABSTRACT FROM AUTHOR]

Water resources management and planning traditionally focus on visible liquid or blue water. However, green water also maintains social development and ecosystem services. Therefore, blue and green water should be incorporated into the watershed management system for evaluating water resources. To analyze the water resources of the Hanjiang River Basin, the SWAT model was set up using long-term and high-precision geographic data. The methods of wavelet analysis and Pearson's correlation analysis were used to explore the influence mechanism of climate and vegetation changes on the blue and green water flow (BWF and GWF) of the main ecosystems in the basin. The results showed that: (1) The spatial–temporal distribution of the BWF and GWF in the main ecosystems of the basin over the past 50 years was uneven. Forest ecosystems and farmland ecosystems have a greater concentration of water resources in the south, while grassland ecosystems have a greater concentration of water resources in the east. (2) Climate dominates the BWF and GWF changes in the main ecosystems of the basin. The BWF and the precipitation change cycle are synergistic, and the GWF and the temperature change cycle are synergistic. (3) The correlation between vegetation and BWF and GWF in the farmland ecosystem is significant. Vegetation affects the hydrological change process of the BWF and GWF at the microscale. This study can provide data support and scientific rules for ecosystem water resource management in the basin. [ABSTRACT FROM AUTHOR]

Frequent droughts may have negative influences on the ecosystem (i.e., terrestrial vegetation) under a warming climate condition. In this study, the linear regression method was first used to analyze trends in vegetation change (normalized difference vegetation index (NDVI)) and drought indices (Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)). The Pearson Correlation analysis was then used to quantify drought impacts on terrestrial vegetation in the Weihe River Basin (WRB); in particular, the response time of vegetation to multiple time scales of drought (RTVD) in the WRB was also investigated. The trend analysis results indicated that 89.77% of the area of the basin showed a significant increasing trend in NDVI from 2000 to 2019. There were also significant variations in NDVI during the year, with the highest rate in June (0.01) and the lowest rate in January (0.002). From 2000 to 2019, SPI and SPEI at different time scales in the WRB showed an overall increasing trend, which indicated that the drought was alleviated. The results of correlation analysis showed that the response time of vegetation to drought in the WRB from 2000 to 2019 was significantly spatially heterogeneous. For NDVI to SPEI, the response time of 12 months was widely distributed in the north; however, the response time of 24 months was mainly distributed in the middle basin. The response time of NDVI to SPI was short and was mainly concentrated at 3 and 6 months; in detail, the response time of 3 months was mainly distributed in the east, while a response time of 6 months was widely distributed in the west. In autumn and winter, the response time of NDVI to SPEI was longer (12 and 24 months), while the response time of NDVI to SPI was shorter (3 months). From the maximum correlation coefficient, the response of grassland to drought (SPEI and SPI) at different time scales (i.e., 6, 12, and 24 months) was higher than that of cultivated land, forestland, and artificial surface. The results may help improve our understanding of the impacts of climatic changes on vegetation cover. [ABSTRACT FROM AUTHOR]

Along with tree ring width, carbon isotopes are also good proxies for climate change. Water use efficiency (WUE) can be calculated more quickly and accurately based on carbon isotopes. In this study, according to the principle of dendroclimatology, the sequence of δ13C and WUE of tree rings of Picea meyeri are built. Pearson correlation analysis and multiple regression analysis are used to explore the response of carbon stable isotopes of Picea meyeri to climate change, which revealed the relationship between δ13C of Picea meyeri and climatic factors. Based on δ13C, we calculated the WUE of Picea meyeri and analyzed its response to climate change. The main conclusions are as follows: (1) The δ13C of Picea meyeri decreases year-by-year from 1957 to 2020, in the range from −23.89‰~−21.67‰, and the average value is −22.67‰. The water use efficiency of Picea meyeri increases in the range from 17.26~61.31, with an average of 39.45. (2) The δ13C of Picea meyeri is negatively correlated with temperature, which has the highest correlation with the temperature of the growing season (c5–c9), and its coefficient is higher than that of the mean temperature of each month. (3) There is a significant positive correlation between WUE sequence and temperature. Meanwhile, due to the effect of precipitation and temperature, the Picea meyeri is subject to drought stress to some extent. Above all, temperature is the main climatic factor affecting the δ13C and WUE of Picea meyeri on Luya mountain. [ABSTRACT FROM AUTHOR]

Global warming poses an enormous threat to particular species with shifts to their suitable habitat. Juniperus rigida Sieb. et Zucc., an endemic species to East Asia and a pioneer species in the Loess plateau region, is endangered because of the shrinking and scattered habitat threatened by climate change. For the sake of analyzing the impact of climate warming on its possible habitat, we herein projected the current and future potential habitats of J. rigida in China and comparatively analyzed the ecological habitat changes in three main distribution regions. There were 110 specimen records of J. rigida collected across China and 22 environmental datasets, including bioclimatic variables and soil and topographical factors, selected by the Pearson Correlation Coefficient. The MaxEnt model based on specimen presence and environmental factors was used for projecting the potential habitats of J. rigida in China in the 2050s and the 2070s of RCP 2.6 and RCP 8.5 scenarios. The results indicated an excellence model performance with the average value of the area under curve (AUC) is 0.928. The mean temperature of the driest quarter (MTDq) and the temperature annual range (TAR) provided important contributions to the potential distribution of J. rigida. There were three main distribution areas in China, the Xinjiang region, the Loess-Inner Mongolian Plateau region, and the Changbai Mountain region. The distribution increased overall in area under RCP 2.6 and decreased for RCP 8.5. The mean altitude of the core distribution shifted upward in general under both scenarios. The Loess–Inner Mongolian Plateau region is the biggest distribution, encompassing ca. 61.39 × 104 km2 (86.87 × 104 km2 in China). The region threatened most by climate change is located in the Changbai Mountain distribution, with the centroid of the cord suitable habitat migrating southwest about 227.47 and 260.32 km under RCP 2.6 and RCP 8.5 by the 2070s. In summary, these findings provided a well-grounded understanding of the effect of climate change on ecological distribution and furnished theory evidence for the protection, management, and sustainable use of J. rigida. [ABSTRACT FROM AUTHOR]

Baseflow is a critical component of streamflow in arid areas. Determining variations in baseflow and the factors affecting it have positive roles for water resource utilization in arid watersheds. Two watersheds, the Hailiutu River watershed (HLTR) and the Dali River watershed (DLR), located in two different geomorphological regions of the middle Yellow River, were selected for this study. By using the Eckhardt segment method (fourth digital filtering method, DF4), baseflow was separated from streamflow based on its daily data. Mann-Kendall trend test analysis (M-K trend test) was used to test the trends in baseflow change at different times. Complex Morlet wavelet analysis was used to judge baseflow periodicity. Heuristic segmentation and sequential cluster analysis were used to identify the potential change points in the baseflow series for the two regions together with Pearson correlation coefficient. The results showed: (1) the annual baseflow of the HLTR and the DLR showed significantly decreasing trends (P < 0.01), more significantly for the HLTR (0.33 × 108 m3) than the DLR (0.20 × 108 m3). The annual base flow index (BFI, baseflow/total streamflow) in the wind-sand region (0.75) was larger than for the loess region (0.55), and the BFI in the wind-sand region was more stable in different periods. (2) The annual baseflow of the HLTR and the DLR both exhibited a complete main cycle of 42 years and 38 years, respectively. The change points of the annual baseflow in the HLTR were 1967 and 1986, and 1971 and 1996 in the DLR. (3) There was no significant change in annual precipitation in the two watersheds, while annual reference evapotranspiration (ET0) in the DLR showed a significant increasing trend (P < 0.01). The normalized difference vegetation index (NDVI) on the DLR (0.40) was higher than on the HLTR (0.26). (4) Baseflow in the wind-sand region, where vegetation improvement was the only ecological activity, decreased faster than in the loess region where there had been numerous ecological measures such as vegetation improvement, check dams and terraces. This implied that comprehensive measures such as these were helpful in slowing the rate at which the baseflow decreases. Therefore, the effect of ecological construction should be considered in future baseflow studies in other geomorphological types within the Middle Yellow River Basin. [ABSTRACT FROM AUTHOR]